Simulation Study on a New Peer Review Approach
Albert Steppi, Jinchan Qu, Minjing Tao, Tingting Zhao, Xiaodong Pang,, Jinfeng Zhang

TL;DR
This study evaluates a new distributed peer review system through simulations, introducing a novel ranking method called CIGR, and proposes strategies to improve review quality and efficiency in scientific assessments.
Contribution
The paper introduces CIGR, a new global ranking method, and a balanced review assignment procedure, along with a multi-stage DPR strategy to enhance review quality and reduce workload.
Findings
CIGR outperforms MBC with high review quality.
Balanced review assignment improves ranking accuracy.
Multi-stage DPR strategy enhances review efficiency.
Abstract
The increasing volume of scientific publications and grant proposals has generated an unprecedentedly high workload to scientific communities. Consequently, review quality has been decreasing and review outcomes have become less correlated with the real merits of the papers and proposals. A novel distributed peer review (DPR) approach has recently been proposed to address these issues. The new approach assigns principal investigators (PIs) who submitted proposals (or papers) to the same program as reviewers. Each PI reviews and ranks a small number (such as seven) of other PIs' proposals. The individual rankings are then used to estimate a global ranking of all proposals using the Modified Borda Count (MBC). In this study, we perform simulation studies to investigate several parameters important for the decision making when adopting this new approach. We also propose a new method called…
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Taxonomy
TopicsExpert finding and Q&A systems · Recommender Systems and Techniques · Scientific Computing and Data Management
